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Making Sense of Multi-dimensional Data with Reduced-Dimensionality Projections and Parallel Coordinates

  • Full or part time
  • Application Deadline
    Monday, April 01, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

There is a great deal of recent and ongoing computer science research developing algorithms for the projection of multi-dimensional data on to 2-D or 3-D space, resulting in scatter-plots that represent the similarity between pairs of items, and can be thought of as offering flexible human-computer clustering algorithms (e.g. LAMP, tSNE).

There is much less research on how these projections can be presented and extended so as to be optimised for human use. This project will explore the interactive coordination of Reduced-Dimensionality Scatter Plots, with Parallel Coordinates. Again, however, there is little systematic work about how parallel coordinate plots are interpreted by data scientists, and how their affordances can be supported by interactive features.

The supervisor and his colleagues at the University of Sao Paul, Brazil, have developed software that allows the user to choose from an array of mutlidimensional projection techniques and inspect these together with an interactively coupled parallel coordinate representation. This PhD will conduct experimental evaluations of this software with various datasets to gain more insight into the uncertainty inherent in the projection techniques, how users can deal with this, and how users can utilise the coordinated representations to gain insight into the structure of the data. According to the student’s interests the project might be mostly experimental-psychology-based or include further developments of the software.

Because the interpretation of high-dimensional data is so central to many contemporary problems, any contribution which helps people to maximally benefit from the advanced mathematical techniques that have been generated in the AI and InfoVis communities has strong potential benefits in political discourse and policy as well as in science and engineering.

This project is associated with the UKRI CDT in Accountable, Responsible and Transparent AI (ART-AI), which is looking for its first cohort of at least 10 students to start in September 2019. Students will be fully funded for 4 years (stipend, UK/EU tuition fees and research support budget). Further details can be found at:

Desirable qualities in candidates include intellectual curiosity, a strong background in maths and programming experience.

Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree. A master’s level qualification would also be advantageous.

Informal enquiries about the project should be directed to Prof Stephen Payne: .

Enquiries about the application process should be sent to .

Formal applications should be made via the University of Bath’s online application form for a PhD in Computer Science:

Start date: 23 September 2019.

Funding Notes

ART-AI CDT studentships are available on a competition basis for UK and EU students for up to 4 years. Funding will cover UK/EU tuition fees as well as providing maintenance at the UKRI doctoral stipend rate (£15,009 per annum for 2019/20) and a training support fee of £1,000 per annum.

We also welcome all-year-round applications from self-funded candidates and candidates who can source their own funding.

How good is research at University of Bath in Computer Science and Informatics?

FTE Category A staff submitted: 24.00

Research output data provided by the Research Excellence Framework (REF)

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